Predictive Maintenance – practical issues

 and scientific challenges

12 February 2024 | Online | 11:00 |  Tiedo Tinga (Netherlands Defence Academy (NLDA) and University of Twente)

To guarantee the availability of critical systems and reduce the associated maintenance costs, many companies invest in the development of smart maintenance concepts, with Predictive Maintenance (PdM) as the ultimate goal. The ever increasing availability of sensor data and fast evolution of artificial intelligence (AI) algorithms facilitate these developments. However, although the promises and expectations for PdM have been sky-high, many companies also experience that application in practice is not always that easy. This tutorial will introduce the main concepts of Predictive Maintenance, and will then discuss a number a practical issues, mainly related to data availability. It will also introduce some directions for scientific research to tackle these. Finally, a range of cases studies form the research program of the speaker will be shown, to demonstrate how these concepts can be implemented in practice.

Tiedo Tinga is full professor Life Cycle Management at the Netherlands Defence Academy (NLDA) in Den Helder, as well as full professor Dynamics based Maintenance at the Engineering Technology department of the University of Twente. He holds a MSc in Material Science from the University of Groningen, aPDEng in Materials Technology from TU Delft and a PhD in computational mechanics from Eindhoven University of Technology. Tingahas been working with the National Aerospace Laboratory NLR for 10 years as a senior scientist. He was involved in research projects on structural integrity,fracture mechanics, computational mechanics and life prediction. In 2007 hejoined the Netherlands Defence Academy as associate professor MaintenanceTechnology. There he is involved in educating the future officers of the DutchAir Force, Army and Navy, and also leads a number of research projects onpredictive maintenance. Since 2012, he combines this position with thepart-time full professorship at the University of Twente. Since 2020 he alsoleads the Knowledge Center Smart Maintenance at the Royal Netherlands Navy,aiming to apply new maintenance technologies in practical cases.

Hisresearch focuses on improving the predictability of failures, aiming to improvepreventive maintenance processes and to develop advanced predictive maintenanceconcepts. The research has a solid basis in understanding and modelling thephysics of failure, which is combined with the development of advanced healthand condition monitoring techniques and data analysis procedures. The researchis applied to assets in various sectors of industry, including defence, transport, aerospace, maritime, process industry and infrastructure. Tiedonow leads research programs on maintenance at both institutes and has been (co-)supervising 30 PhD and PDEng students in the past 10 years. Tiedo has publishedaround 100 papers in international ISI journals and conferences. He has alsobeen actively involved in the initiation (funding) and execution of manyresearch projects, which are in close cooperation with industry and scientificpartners.